• 제목/요약/키워드: ToA estimation

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구조설계정보 통합 관리에 의한 철근 물량 산출 자동화 기초 연구 (Basic study about Automatic Rebar Quantity Estimation Integrated with Structural Design Information)

  • 성수진;임채연;김선국
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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    • pp.109-110
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    • 2015
  • Estimation of rebar quantity may be used as an index to evaluate the economic feasibility of structural designs. However, when using the software to estimate the rebar quantity, there may be some limitations such as data loss caused by human errors and estimation delays caused by increased input time, since the information on arrangement of rebar is inserted manually. To solve the problems of such quantity estimation software, it is necessary to develop a method on automatic input/output of structural design information for quantity estimation and an algorithm for accurate estimation of rebar quantity. The purpose of this study is to improve the existing rebar quantity estimation by connecting with the database on information related to rebar estimation and the algorithm for rebar estimation, in order to develop an algorithm to estimate an accurate, net rebar quantity. The study result can be used as basic data for development of software for efficient structural designs and automatic framework estimation of buildings.

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덧셈과 뺄셈의 어림셈 지도 방식에 대한 다차원 교육과정적 관점에서의 논의 (A discussion from a multi-dimensional curriculum perspective on how to instruct the computational estimation of addition and subtraction)

  • 도주원;백석윤
    • 한국수학교육학회지시리즈A:수학교육
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    • 제59권3호
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    • pp.255-269
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    • 2020
  • 본 연구에서는 의도-작성-실행된 교육과정이라는 일련의 다차원 교육과정적 관점에서 초등 수학의 연산 중 기본이 되는 덧셈과 뺄셈의 어림셈 지도 방식에 대하여 논의하였다. 실행된 교육과정에서 출발하여 작성-의도된 교육과정의 상향식 피드백 방식으로 덧셈과 뺄셈의 어림셈 지도에 대한 교수·학습 방법 면에서의 쟁점 사항을 파악하고 이를 개선하기 위한 시사점을 도출하였다.

소프트웨어 사업대가기준 중장기 발전 방향에 관한 연구 (A Study on the Mid-Long Term Direction for Development of Software Cost Estimation Guidelines)

  • 김우제;권문주
    • 한국전자거래학회지
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    • 제15권1호
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    • pp.139-155
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    • 2010
  • 본 논문의 목적은 소프트웨어 사업대가기준의 중장기 발전 방향을 도출하고 소프트웨어 사업대가기준의 프레임워크를 제시하는 것이다. 본 논문에서는 첫째, 소프트웨어 생명주기상의 모든 단계와 현재의 소프트웨어 사업대가기준과 모형들이 검토되고 분석되어졌다. 둘째, 소프트웨어 사업대가기준의 중장기적 발전 대안으로 단가와 지침을 분리하여 운영하고, 시장자율기능을 확대하는 방안을 도출하였다. 그리고 소프트웨어 사업대가기준의 중장기 발전대안의 선결과제로 비용 리포지토리의 구축, 소프트웨어 사업대가 지침화, 다양한 사업대가기준 모형화 및 인증제 도입, 사업대가 전문가제도 도입이 제시되었다. 마지막으로 소프트웨어 사업대가기준의 중장기 발전대안의 단계별 이행계획이 제시되었다.

A Fuzzy Logic Based Software Development Cost Estimation Model with improved Accuracy

  • Shrabani Mallick;Dharmender Singh Kushwaha
    • International Journal of Computer Science & Network Security
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    • 제24권6호
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    • pp.17-22
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    • 2024
  • Software cost and schedule estimation is usually based on the estimated size of the software. Advanced estimation techniques also make use of the diverse factors viz, nature of the project, staff skills available, time constraints, performance constraints, technology required and so on. Usually, estimation is based on an estimation model prepared with the help of experienced project managers. Estimation of software cost is predominantly a crucial activity as it incurs huge economic and strategic investment. However accurate estimation still remains a challenge as the algorithmic models used for Software Project planning and Estimation doesn't address the true dynamic nature of Software Development. This paper presents an efficient approach using the contemporary Constructive Cost Model (COCOMO) augmented with the desirable feature of fuzzy logic to address the uncertainty and flexibility associated with the cost drivers (Effort Multiplier Factor). The approach has been validated and interpreted by project experts and shows convincing results as compared to simple algorithmic models.

2단계 신경망 추정에 의한 와이어 컷 방전 가공 조건 선정 (Selection of Machining Parameters of Electric Discharge Wire Cut Using 2-Step Neuro-estimation)

  • 이건범;주상윤;왕지남
    • 산업공학
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    • 제10권3호
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    • pp.125-132
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    • 1997
  • We proposed a 2-step neural network approach for estimating machining parameters of electric discharge wire cut. The first step net, which is described as a backward neuro-estimation, is designed for estimating coarse cutting parameters while the second phase net, as a polishing forward neuro-estimation, is utilized for determining fine parameters. Sequential estimation procedure, based on backward and forward net, is performed using the net's approximation capability which is M to 1 and 1 to M mapping property. Experimental results an given to evaluate the accuracy of the proposed 2-step neuro-estimation.

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액상화.영구지반변형을 고려한 지중매설관로의 지진피해 평가 (Earthquake Loss Estimation of Buried Pipeline Considering Permanent Ground Deformation due to Liquefaction)

  • 김태욱;임윤묵;김문겸
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2005년도 학술발표회 논문집
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    • pp.102-109
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    • 2005
  • In this study, a prototype model of earthquake loss estimation method will be proposed for the quantitative and qualitative damage evaluation of buried pipeline subjected to Permanent Ground Deformation(PGD) due to liquefaction. With this objective, domestic and foreign status of the arts related with earthquake loss estimation method is summarized at first. Domestic development of computer aided earthquake loss estimation method seems to be difficult for the time being. Thus, referring to HAZUS : Earthquake Loss Estimation Methodology which is developed by FEMA (Federal Emergency Management Agency) and NIBS (National Institute of Building Sciences), earthquake loss estimation procedure of buried pipeline subjected to PGD due to liquefaction are proposed, and then exemplary loss estimation are executed. Considering that there have been no practical earthquake loss estimation method and procedure in Korea, the research accomplishments such as above are considered to be helpful for the substantial development of earthquake loss estimation method of buried pipeline subjected to PGD due to liquefaction.

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Robust 2D human upper-body pose estimation with fully convolutional network

  • Lee, Seunghee;Koo, Jungmo;Kim, Jinki;Myung, Hyun
    • Advances in robotics research
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    • 제2권2호
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    • pp.129-140
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    • 2018
  • With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

Efficient distributed estimation based on non-regular quantized data

  • Kim, Yoon Hak
    • 전기전자학회논문지
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    • 제23권2호
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    • pp.710-715
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    • 2019
  • We consider parameter estimation in distributed systems in which measurements at local nodes are quantized in a non-regular manner, where multiple codewords are mapped into a single local measurement. For the system with non-regular quantization, to ensure a perfect independent encoding at local nodes, a local measurement can be encoded into a set of a great number of codewords which are transmitted to a fusion node where estimation is conducted with enormous computational cost due to the large cardinality of the sets. In this paper, we propose an efficient estimation technique that can handle the non-regular quantized data by efficiently finding the feasible combination of codewords without searching all of the possible combinations. We conduct experiments to show that the proposed estimation performs well with respect to previous novel techniques with a reasonable complexity.

센서네트워크 내의 IV 기법과 QCLS 기법을 결합한 위치 추정 (Target Localization using Combination of the IV and QCLS Method in the Sensor Network)

  • 김용휘;최가형;윤태성;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.1768-1769
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    • 2011
  • The nonlinear estimation and the pseudo-linear estimation are used to treat the target localization in sensor network which provides range difference of arrival (RDOA) measurements. It is known that the nonlinear estimation has sensitive problem for the initial estimate and the pseudo-linear estimation has a large estimation error. The QCLS method is the typical estimator of the methods for pseudo-linear estimation. However the estimate by using the QCLS method includes the estimation error because the first stage of two estimation processes of the QCLS method causes the biased estimation error. Therefore we propose a instrumental variables(IV) method for minimizing the estimation error of the first stage. The simulation shows that the performance of the proposed method is superior to the QCLS method.

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GPU-Accelerated Single Image Depth Estimation with Color-Filtered Aperture

  • Hsu, Yueh-Teng;Chen, Chun-Chieh;Tseng, Shu-Ming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권3호
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    • pp.1058-1070
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    • 2014
  • There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.